"Windows Performance Toolkit and xperf.exe" matching MCP servers:

Enables AI agents to inspect why React components re-rendered, replay recorded browser interactions as performance scenarios in headless Chrome, and verify fixes against performance budgets.

Converts non-functional requirements and code into secure, traceable JMeter performance tests with coverage analysis, plan generation, execution, and GitHub draft PRs.

Enables AI agents to control and interact with the Windows operating system, including file navigation, application control, UI automation, and QA testing.

Enables AI agents to seamlessly integrate with the Windows operating system, performing tasks such as file navigation, application control, UI interaction, and QA testing via the MCP protocol.

Checks a repository's own guardrails and fails any that are present but have stopped refusing anything. Three read-only tools: installation status, per-step verification that issues a receipt, and a tail of the append-only ledger recording every question and answer.

Enables AI agents to perform WCAG 2.2 accessibility audits, including contrast ratio checks for color pairs and text-over-image, generate EU legal accessibility declarations, and produce aria-live monitoring snippets, all through local, multilingual tools.

9 MCP servers for React + TypeScript development automation — component scaffolding, dependency auditing, WCAG accessibility checking, test generation, TypeScript enforcement, and monorepo management. 134 tests, CI on Node 20+22.

Provides utilities to help maintain MCP repositories, including testing tools, parameter type support, and multiple transports (STDIO, SSE, Streamable HTTP).

Enables AI agents to inspect Unity UI Toolkit screens, examine element structure and styles, and capture screenshots without entering Play Mode or building a Player.

Enables AI agents to create webhook URLs, wait for incoming deliveries, inspect payloads, and replay or send signed webhook events to a local handler.

An MCP server that reads test reports and provides regression analysis tools for comparing runs, identifying regressions, fixes, and persistent failures.

Provides coding agents with visibility into test health through tools for flaky test detection, test quality linting, and LLM evaluation harness, enabling them to triage failures, review test quality, and check prompt changes for regressions.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Comprehensive MCP server for end-to-end UI development, offering tools to generate components, manage design tokens, audit accessibility, autofix issues, inspect live pages, compare screenshots, and more across multiple frameworks.

Enables AI assistants to automate Godot 4 projects via headless tooling, live editor control, and runtime remote control, including scene building, testing, and observation.

Enables regex testing, replacement, splitting, validation, explanation, escaping, common patterns, and benchmarking through an MCP server.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

Enables AI coding agents to build, test, lint, and debug Android projects with concise Gradle output, filtered logcat, and connected-device inspection and interaction. It also supports setup across several agent clients and caps noisy output to save tokens.

Real-time Core Web Vitals (LCP) telemetry, DOM bloat analysis, and AI search crawler (GEO) readiness audits for AI coding assistants.

Enables users to query, create, update, and manage Digital.ai Agility assets through MCP tools, with secure Windows Credential Manager authentication and configurable write operations.

Enables MCP clients to retrieve lab performance scores and field Core Web Vitals data for web pages via Google APIs.

An MCP server that analyzes SQL schemas, generates realistic test data, benchmarks queries, and provides optimization recommendations to improve database performance.

Enables step-through debugging for C#, Node.js/TypeScript, Python, and Dart applications on Windows through a unified MCP interface. Acts as a bridge between MCP clients and various debug adapters, providing consistent debugging workflows with breakpoints, variable inspection, and process attachment capabilities.

Enables LLMs to interact directly with generated REST services by discovering and invoking CRUD tools and reading exposed resources for list and get-by-id data.

Validates .mcp.json and claude_desktop_config files to catch duplicate server names, missing binaries, invalid environment variables, and unreachable endpoints. Reports each problem along with how to fix it, so silently failing MCP servers can be diagnosed and repaired.

Enables OpenCode to safely automate and verify Windows desktop and web browser interactions through 83 MCP tools, including UI automation, screenshots, visual diffing, workflow recording, and secret handling, with strict allowlist-based security.

Enables users to run synthetic support-agent evaluations, preserve and inspect traces, score results deterministically, inject failures, and enforce release review gates through MCP tools, resources, and prompts.

Enables building and testing Model Context Protocol servers with a decorator-based API, in-process JSON-RPC test client, and 14-check protocol conformance report.

Windows桌面截图与窗口自动化工具，支持后台操作、不抢焦点，可截取窗口/屏幕、模拟鼠标键盘、点击菜单等。

Provides a framework for running multiple MCP servers using FastAPI, stdio, and streamable-http transports, with an echo tool for testing and integration with MCP Inspector.